After a couple of months off, I am restarting the weekly round-up with the aim of truly being weekly — Monday nights to be precise. Welcome back.

Let’s face it – this week it has been nigh on impossible to focus on anything other than the new administration. There have been some genomics related happenings:

• Berkeley geneticist Michael Eisen has announced he is running for the senate, likely as an independent, because the new administration’s attitude of “basic rejection of the fundamental principles upon which science is based”
• Trump announcedto pharma execs that his main focus for the FDA will be on improving time to market through decreased regulation. This has many in biotech concerned that hard won consumer protections may be lost, and that startups will not be able to compete alongside the pharma giants. Trump’s pick for the top job at the agency should be announced soon.
• Meanwhile, although Biotech executives were quick to condemn the immigration ban, pharma execs were mostly quiet— perhaps because Trump thinks they’re “getting away with murder” on pricing, and are hence not wanting to rock the boot.

Despite being dropped by Roche last year, PacBio claims to be doing well. They improved the chemistry to the point at which de novo assemblies (i.e. with no reference genome) became feasible on their Sequel machines. Meanwhile BGI has announced that 2017 will be the year that the tech it bought from Complete Genomics really starts delivering. They will first deliver quantitative RNA-seq on their BGISEQ-500, with plans later in the year to deliver a $600 whole genome.

The MedSeq project, who performed WGS on 100 healthy people and 100 cardiomyopathy patients, has reported that 6 months after sequencing, those who had received WGS results has not cost their health care systems much more than those who had not. This is one of the very few studies providing data on the cost and benefits of WES/WGS. A major worry that payors have is that NGS testing will spark a flurry of expensive follow on tests.

Heidi Rehm weighs in on how low cost sequencing will impact health care. The usual emphasis on the importance of data sharing and models to encourage that. This sentence was thought provoking, “Although genetic counsellors will undoubtedly be critical in this space, it will also become increasingly important to facilitate knowledge-building through online tools and for individuals to take an active role in educating themselves about genetics.” What shape should these online tools take, who should build them, and how to encourage people to take an active role in educating themselves?

Over the last couple of weeks there have been a couple of events to show how seriously gene editing is being taken:

• The ACMG published a Statement on Jan 26th 2017: “Genome editing is an area of very rapid technological change, so what is not possible today could well become a reality in the very near future… The potential for rapid advance of this approach, and the pressure to apply it clinically, should not be underestimated. The ACMG Board of Directors strongly encourages broad public debate regarding the clinical application of genomic editing.”  They also call out application to nondisease traits.
• The FDA publishedits intent to regulate genetically modified animals in the same way they do drugs. This has not been popular.

 

Science – mostly association studies

Height has high heritability — 60-80% of variance in height is accounted for by genetics. We are moving from the world of genetic association studies that could only investigate common variants to the ability to probe rarer variants throughout the genome. When it comes to height, the work of the Genetic Investigation of Anthropometric Traits (GIANT) Consortium spans these approaches

• In the first iteration of work in 2014, GIANT had focused on polymorphisms — variants that are common (>5%) in the population. They found 700 such variants associated with height, the effect size for any given variant was ~1mm. This work lead to ~20% of heritability of height being explained.
• In their just publishedsecond iteration, GIANT focused on rarer variants (<5%, >0.01%) in protein coding genes, and found 83 variants, some of which contributed >2cm (nearly 1 inch) if height. Rarer variants like this are harder to study because you need larger sample sizes (this study used >700,000 people), but the rewards pay off. Now ~27% of heritability of height is explained.

This approach still used a chip design (rather than NGS). Explaining more of the heritability will come from larger sample sizes on the one hand, and looking at more of the genome on the other.

Meanwhile, a Chinese team has reported the first general population genome wide significant SNPs associated with mathematical ability, using a chip based assay to get at variants down to 2% frequency. Four SNPs in the SPOCK1 gene each effect match scores by 2.33-2.43 points. (The name of the gene seems very apt, though the high-functioning Vulcan was not the inspiration for the name). The motivation for getting at the genetic underpinnings of intelligence according to the authors: “Understanding mathematics ability is an essential step to improve children’s numeracy skills and academic achievements and could also provide novel insights into human brain functions.” This study is one of many in China focused on the genetic underpinnings of intelligence, something we in the West have far more “hang-ups” about studying.

Another large association study was published this week, this one on the genetic underpinnings of blood pressure. Part of the UK BioBank, this study used an exome chip (for variants down to 0.01%) as well as a SNP array (for variants down to 1%) and looked at over >140,000 individuals.

A study of 1463 whole genomes from Finnish individuals compared to the same number of British individuals reveals some of the hallmarks of population bottlenecks, including more loss of function variants in the Finnish population.

The Dana-Farber Cancer Institute reports on their experience of WES for cancer patients, looking at both germline and somatic variants. “The variant review and decision-making processes were effective when the process was changed from that of a Molecular Tumor Board to a protocol-based approach.”

CIViC, a community knowledgebase for expert crowdsourcing the clinical interpretation of variants in cancer, has published a summary of their efforts to date: there are 1,678 clinically relevant curated interpretations of 713 variants affecting 283 genes, using 1,077 publications, and performed by 58 curators. They are dedicated to openness (cough cough HGMD).

Move aside genomics: a review of blood-based proteomics in setting cancer treatment